Background: Persistent neurological and cognitive symptoms following SARS-CoV-2 infection point to long-term alterations in brain structure and function. The thalamus, orbitofrontal cortex, and limbic networks are particularly susceptible to inflammatory and neurovascular stressors. However, the relationship between cortical, white-matter, and thalamocortical alterations in post-COVID syndrome remains unclear. Methods: 76 COVID-19 recovered participants (CRPs) and 51 healthy controls (HCs) underwent multimodal MRI comprising T1-weighted structural, diffusion, and resting-state functional acquisitions. Grey-matter morphology was assessed using voxel-based morphometry (VBM), white-matter microstructure using tract-based spatial statistics (TBSS), and thalamocortical functional connectivity (TC-FC) using seed-based analyses from major thalamic nuclei. Results were evaluated both across the groups (HC vs. CRP) and after stratifying CRPs by hospitalisation status (HC vs. Non-hospitalized patients (NHPs) vs. Hospitalized patients (HPs)). Results: No group-level grey-matter differences were observed between HCs and CRPs; however, HPs showed localized volume loss in the orbitofrontal and frontal-pole cortices (pFWE < 0.05). TBSS revealed widespread microstructural abnormalities, including reduced fractional anisotropy and mean diffusivity across association and commissural tracts (pcorr < 0.05), with regional increases in mode of anisotropy indicating selective loss of crossing fibres (pcorr < 0.05). Resting-state analyses revealed increased TC-FC from the mediodorsal thalamic nucleus to anterior cingulate, parietal, and occipital cortices (pcorr < 0.05), while differences in pulvinar and ventrolateral nuclei were not significant (pcorr > 0.05). Conclusions: Our findings indicate that COVID-19 recovery is associated with enduring alterations in fronto-limbic and thalamo-cortical circuits, most prominently in individuals with severe infection. Convergent structural and functional changes involving the orbitofrontal cortex and mediodorsal thalamus suggest network-specific reorganisation that may underpin persistent cognitive and affective symptoms of post-COVID syndrome. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This study was supported by the Ministry of Electronics and Information Technology (MeitY), Government of India, under grant number 4(16)/2019-ITEA, and by the Cadence Chair Professor fund awarded to Dr. Tapan Kumar Gandhi. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of Indian Institute of Technology (IIT) Delhi gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes The dataset will be made available upon reasonable request to the corresponding authors, subject to institutional data-sharing policies. Ministry of Electronics and Information Technology, https://ror.org/02z31cn83

UK Biobank is the world's most comprehensive longitudinal population-based data and biosample resource. Twenty years after UK Biobank was first established, the incidence of dementia among participants is rising and is set to increase rapidly over the next 5-10 years, creating a distinct opportunity for studies of dementia risk and onset. In addition to extensive clinical phenotyping of >500,000 volunteers from across the UK at recruitment and at follow-up time points, UK Biobank includes data from serial lifestyle questionnaires, cognitive testing, multimodal imaging, accelerometry, genomics and other omics that are linked to individual health, cancer and death records. In this Perspective, we discuss how the use of UK Biobank data has enabled the discovery of new interactions between systemic and brain health and illustrate how these data can be used to characterize and identify risk factors, support mechanistic hypotheses and identify new biomarkers that predict the onset and course of dementia and related disorders. We also consider future developments of UK Biobank, including the UK Biobank Brain Health Study, which will build on and leverage the increasing incidence of dementias to advance understanding of these conditions.

The hypothalamus, pituitary gland and olfactory bulbs are neuro-anatomical structures key to the regulation of the endocrine system. Variation in their anatomy can affect the function of the reproductive system. To investigate this relationship, we extracted four largely unexplored phenotypes from 34,834 individuals within UK Biobank by quantifying the volume of the hypothalamus, pituitary gland and olfactory bulbs using multi-modal magnetic resonance imaging. Genome-wide association studies of these phenotypes identified 66 independent common genetic associations with endocrine-related neurological volumes ( P < 5 × 10−8), five of which had a prior association to testosterone levels, representing enrichment of testosterone-associated SNPs over random chance ( P -value = 9.89 × 10−12). Exome-wide rare variant burden analysis identified STAB1 as being significantly associated with hypothalamus volume ( P = 3.78 × 10−7), with known associations to brain iron levels. Common variants associated with hypothalamic grey matter volume were also found to be associated with iron metabolism, in which testosterone plays a key role. These results provide initial evidence of common and rare genetic effects on both anatomical variation in neuroendocrine structures and their function in hormone production and regulation. Variants associated with pituitary gland volume were enriched for gene expression specific to theca cells, responsible for testosterone production in ovaries, suggesting shared underlying genetic variation affecting both neurological and gonadal endocrine tissues. Cell-type expression enrichment analysis across hypothalamic cell types identified tanycytes to be associated ( P = 1.69 × 10−3) with olfactory bulb volume associated genetic variants, a cell type involved in release of gonadotropin-releasing hormone into the bloodstream. Voxel-wise analysis highlighted associations between the variants associated with pituitary gland volume and regions of the brain involved in the drainage of hormones into the bloodstream. Together, our results suggest a shared role of genetics impacting both the anatomy and function of neuroendocrine structures within the reproductive system in their production and release of reproductive hormones. ### Competing Interest Statement SB has ownerships in Intomics A/S, Hoba Therapeutics Aps, Novo Nordisk A/S, Lundbeck A/S, ALK abello A/S, Eli Lilly and Co and managing board memberships in Proscion A/S and Intomics A/S. CML reports grants from Bayer AG and Novo Nordisk and has a partner who works at Vertex. ### Funding Statement HC was funded by the European Union under a Marie Skłodowska-Curie Postdoctoral Fellowship, Project 101064250, RMCmplxPheno. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or Horizon Europe. Neither the European Union nor the granting authority can be held responsible for them. CA, SMS and FJL recieve funding from Wellcome Trust 215573/Z/19/Z and 203139/Z/16/Z. SSV is supported by the Rhodes Scholarships, Clarendon Fund, and the Medical Sciences Doctoral Training Centre at the University of Oxford. NAB is supported by Wellcome Trust 218486/Z/19/Z. YC is supported by NIH P50 HD104224. SB is recieves funding from Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). C.M.L. is supported by the Li Ka Shing Foundation, NIHR Oxford Biomedical Research Centre, Oxford, NIH (1P50HD104224-01), Gates Foundation (INV-024200), and a Wellcome Trust Investigator Award (221782/Z/20/Z). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: UK Biobank has approval from the North West Multi-centre Research Ethics Committee (http://www.ukbiobank.ac.uk/ethics/), which also covers the work in this study. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes Data used within the manuscript is available upon application to the UK Biobank.

We present MMORF—FSL’s MultiMOdal Registration Framework—a newly released nonlinear image registration tool designed primarily for application to MRI images of the brain. MMORF is capable of simultaneously optimising both displacement and rotational transformations within a single registration framework by leveraging rich information from multiple scalar and tensor modalities. The regularisation employed in MMORF promotes local rigidity in the deformation, and we have previously demonstrated how this effectively controls both shape and size distortion, and leads to more biologically plausible warps. The performance of MMORF is benchmarked against three established nonlinear registration methods—FNIRT, ANTs and DR-TAMAS—across four domains: FreeSurfer label overlap, DTI similarity, task-fMRI cluster mass, and distortion. Results show that MMORF performs as well as or better than all other methods across every domain—both in terms of accuracy and levels of distortion. MMORF is available as part of FSL, and its inputs and outputs are fully compatible with existing workflows. We believe that MMORF will be a valuable tool for the neuroimaging community, regardless of the domain of any downstream analysis, providing state-of-the-art registration performance that integrates into the rich and widely adopted suite of analysis tools in FSL.

We have previously identified a network of higher-order brain regions particularly vulnerable to the ageing process, schizophrenia and Alzheimer’s disease. However, it remains unknown what the genetic influences on this fragile brain network are, and whether it can be altered by the most common modifiable risk factors for dementia. Here, in ~40,000 UK Biobank participants, we first show significant genome-wide associations between this brain network and seven genetic clusters implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s disease, and with the two antigens of the XG blood group located in the pseudoautosomal region of the sex chromosomes. We further reveal that the most deleterious modifiable risk factors for this vulnerable brain network are diabetes, nitrogen dioxide – a proxy for traffic-related air pollution – and alcohol intake frequency. The extent of these associations was uncovered by examining these modifiable risk factors in a single model to assess the unique contribution of each on the vulnerable brain network, above and beyond the dominating effects of age and sex. These results provide a comprehensive picture of the role played by genetic and modifiable risk factors on these fragile parts of the brain.

Anatomical magnetic resonance imaging (MRI) templates of the brain are essentialto group-level analyses and image processing pipelines, as they provide areference space for spatial normalisation. While it has become common forstudies to acquire multimodal MRI data, many templates are still limited to onetype of modality, usually either scalar or tensor based. Aligning each modalityin isolation does not take full advantage of the available complementaryinformation, such as strong contrast between tissue types in structural images,or axonal organisation in the white matter in diffusion tensor images. Mostexisting strategies for multimodal template construction either do not use allmodalities of interest to inform the template construction process, or do notuse them in a unified framework. Here, we present multimodal, cross-sectionaltemplates constructed from UK Biobank data: the Oxford-MultiModal-1 (OMM-1)template and age-dependent templates for each year of life between 45 and 81years. All templates are fully unbiased to represent the average shape of thepopulations they were constructed from, and internally consistent throughjointly informing the template construction process with T1-weighted (T1),T2-weighted fluid-attenuated inversion recovery (T2-FLAIR), and diffusion tensorimaging (DTI) data. The OMM-1 template was constructed with a multiresolution,iterative approach using 240 individuals in the 50-55-year age range. Theage-dependent templates were estimated using a Gaussian process, which describesthe change in average brain shape with age in 37,330 individuals. All templatesshow excellent contrast and alignment within and between modalities. The globalbrain shape and size are not preconditioned on existing templates, althoughmaximal possible compatibility with MNI-152 space was maintained through rigidalignment. We showed benefits in registration accuracy across two datasets (UKBiobank and HCP), when using the OMM-1 as the template compared withFSL's MNI-152 template, and found that the use of age-dependent templatesfurther improved accuracy to a small but detectable extent. All templates arepublicly available and can be used as a new reference space for uni- ormultimodal spatial alignment.

Resting-state fMRI studies have shown that multiple functional networks, which consist of distributed brain regions that share synchronised spontaneous activity, co-exist in the brain. As these resting-state networks (RSNs) have been thought to reflect the brain's intrinsic functional organization, intersubject variability in the networks' spontaneous fluctuations may be associated with individuals' clinical, physiological, cognitive, and genetic traits. Here, we investigated resting-state fMRI data along with extensive clinical, lifestyle, and genetic data collected from 37,842 UK Biobank participants, with the object of elucidating intersubject variability in the fluctuation amplitudes of RSNs. Functional properties of the RSN amplitudes were first examined by analyzing correlations with the well-established between-network functional connectivity. It was found that a network amplitude is highly correlated with the mean strength of the functional connectivity that the network has with the other networks. Intersubject clustering analysis showed the amplitudes are most strongly correlated with age, cardiovascular factors, body composition, blood cell counts, lung function, and sex, with some differences in the correlation strengths between sensory and cognitive RSNs. Genome-wide association studies (GWASs) of RSN amplitudes identified several significant genetic variants reported in previous GWASs for their implications in sleep duration. We provide insight into key factors determining RSN amplitudes and demonstrate that intersubject variability of the amplitudes primarily originates from differences in temporal synchrony between functionally linked brain regions, rather than differences in the magnitude of raw voxelwise BOLD signal changes. This finding additionally revealed intriguing differences between sensory and cognitive RSNs with respect to sex effects on temporal synchrony and provided evidence suggesting that synchronous coactivations of functionally linked brain regions, and magnitudes of BOLD signal changes, may be related to different genetic mechanisms. These results underscore that intersubject variability of the amplitudes in health and disease need to be interpreted largely as a measure of the sum of within-network temporal synchrony and amplitudes of BOLD signals, with a dominant contribution from the former.

Huntington's and Parkinson's disease are two movement disorders representing mainly opposite states of the basal ganglia inhibitory function. Despite being an integral part of the cortico-subcortico-cortical circuitry, the subthalamic nucleus function has been studied at the level of detail required to isolate its signal only through invasive studies in Huntington's and Parkinson's disease. Here, we tested whether the subthalamic nucleus exhibited opposite functional signatures in early Huntington's and Parkinson's disease. We included both movement disorders in the same whole-brain imaging study, and leveraged ultra-high-field 7T MRI to achieve the very fine resolution needed to investigate the smallest of the basal ganglia nuclei. Eleven of the 12 Huntington's disease carriers were recruited at a premanifest stage, while 16 of the 18 Parkinson's disease patients only exhibited unilateral motor symptoms (15 were at Stage I of Hoehn and Yahr off medication). Our group comparison interaction analyses, including 24 healthy controls, revealed a differential effect of Huntington's and Parkinson's disease on the functional connectivity at rest of the subthalamic nucleus within the sensorimotor network, i.e. an opposite effect compared with their respective age-matched healthy control groups. This differential impact in the subthalamic nucleus included an area precisely corresponding to the deep brain stimulation 'sweet spot'-the area with maximum overall efficacy-in Parkinson's disease. Importantly, the severity of deviation away from controls' resting-state values in the subthalamic nucleus was associated with the severity of motor and cognitive symptoms in both diseases, despite functional connectivity going in opposite directions in each disorder. We also observed an altered, opposite impact of Huntington's and Parkinson's disease on functional connectivity within the sensorimotor cortex, once again with relevant associations with clinical symptoms. The high resolution offered by the 7T scanner has thus made it possible to explore the complex interplay between the disease effects and their contribution on the subthalamic nucleus, and sensorimotor cortex. Taken altogether, these findings reveal for the first time non-invasively in humans a differential, clinically meaningful impact of the pathophysiological process of these two movement disorders on the overall sensorimotor functional connection of the subthalamic nucleus and sensorimotor cortex.

A key aim in epidemiological neuroscience is identification of markers to assess brain health and monitor therapeutic interventions. Quantitative susceptibility mapping (QSM) is an emerging magnetic resonance imaging technique that measures tissue magnetic susceptibility and has been shown to detect pathological changes in tissue iron, myelin and calcification. We present an open resource of QSM-based imaging measures of multiple brain structures in 35,273 individuals from the UK Biobank prospective epidemiological study. We identify statistically significant associations of 251 phenotypes with magnetic susceptibility that include body iron, disease, diet and alcohol consumption. Genome-wide associations relate magnetic susceptibility to 76 replicating clusters of genetic variants with biological functions involving iron, calcium, myelin and extracellular matrix. These patterns of associations include relationships that are unique to QSM, in particular being complementary to T2* signal decay time measures. These new imaging phenotypes are being integrated into the core UK Biobank measures provided to researchers worldwide, creating the potential to discover new, non-invasive markers of brain health.

Introduction Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King’s College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. Conclusion These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study.

There is strong evidence of brain-related abnormalities in COVID-19(1-13). However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51-81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans-with 141 days on average separating their diagnosis and the second scan-as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up.

Sleep plays a key role in supporting brain function and resilience to brain decline. It is well known that sleep changes substantially with aging and that aging is associated with deterioration of brain structure. In this study, we sought to characterize the relationship between slow wave slope (SWslope)-a key marker of sleep architecture and an indirect proxy of sleep quality-and microstructure of white matter pathways in healthy adults with no sleep complaints. Participants were 12 young (24-27 years) and 12 older (50-79 years) adults. Sleep was assessed with nocturnal electroencephalography (EEG) and the Pittsburgh Sleep Quality Index (PSQI). White matter integrity was assessed using tract-based spatial statistics (TBSS) on tensor-based metrics such as Fractional Anisotropy (FA) and Mean Diffusivity (MD). Global PSQI score did not differ between younger (n = 11) and older (n = 11) adults (U = 50, p = 0.505), but EEG revealed that younger adults had a steeper SWslope at both frontal electrode sites (F3: U = 2, p < 0.001, F4: U = 4, p < 0.001, n = 12 younger, 10 older). There were widespread correlations between various diffusion tensor-based metrics of white matter integrity and sleep SWslope, over and above effects of age (n = 11 younger, 9 older). This was particularly evident for the corpus callosum, corona radiata, superior longitudinal fasciculus, internal and external capsule. This indicates that reduced sleep slow waves may be associated with widespread white matter deterioration. Future studies should investigate whether interventions targeted at improving sleep architecture also impact on decline in white matter microstructure in older adults.

The World Health Organization promotes physical exercise and a healthy lifestyle as means to improve youth development. However, relationships between physical lifestyle and human brain development are not fully understood. Here, we asked whether a human brain–physical latent mode of covariation underpins the relationship between physical activity, fitness, and physical health measures with multimodal neuroimaging markers. In 50 12-year old school pupils (26 females), we acquired multimodal whole-brain MRI, characterizing brain structure, microstructure, function, myelin content, and blood perfusion. We also acquired physical variables measuring objective fitness levels, 7 d physical activity, body mass index, heart rate, and blood pressure. Using canonical correlation analysis, we unravel a latent mode of brain–physical covariation, independent of demographics, school, or socioeconomic status. We show that MRI metrics with greater involvement in this mode also showed spatially extended patterns across the brain. Specifically, global patterns of greater gray matter perfusion, volume, cortical surface area, greater white matter extra-neurite density, and resting state networks activity covaried positively with measures reflecting a physically active phenotype (high fit, low sedentary individuals). Showing that a physically active lifestyle is linked with systems-level brain MRI metrics, these results suggest widespread associations relating to several biological processes. These results support the notion of close brain-body relationships and underline the importance of investigating modifiable lifestyle factors not only for physical health but also for brain health early in adolescence. SIGNIFICANCE STATEMENT An active lifestyle is key for healthy development. In this work, we answer the following question: How do brain neuroimaging markers relate with young adolescents' level of physical activity, fitness, and physical health? Combining advanced whole-brain multimodal MRI metrics with computational approaches, we show a robust relationship between physically active lifestyles and spatially extended, multimodal brain imaging-derived phenotypes. Suggesting a wider effect on brain neuroimaging metrics than previously thought, this work underlies the importance of studying physical lifestyle, as well as other brain–body relationships in an effort to foster brain health at this crucial stage in development.

The first 72 h following aneurysm rupture play a key role in determining clinical and cognitive outcomes after subarachnoid haemorrhage (SAH). Yet, very little is known about the impact of so called “early brain injury” on patents with clinically good grade SAH (as defined as World Federation of Neurosurgeons Grade 1 and 2). 27 patients with good grade SAH underwent MRI scanning were prospectively recruited at three time-points after SAH: within the first 72 h (acute phase), at 5–10 days and at 3 months. Patients underwent additional, comprehensive cognitive assessment 3 months post-SAH. 27 paired healthy controls were also recruited for comparison. In the first 72 h post-SAH, patients had significantly higher global and regional brain volume than controls. This change was accompanied by restricted water diffusion in patients. Persisting abnormalities in the volume of the posterior cerebellum at 3 months post-SAH were present to those patients with worse cognitive outcome. When using this residual abnormal brain area as a region of interest in the acute-phase scans, we could predict with an accuracy of 84% (sensitivity 82%, specificity 86%) which patients would develop cognitive impairment 3 months later, despite initially appearing clinically indistinguishable from those making full recovery. In an exploratory sample of good clinical grade SAH patients compared to healthy controls, we identified a region of the posterior cerebellum for which acute changes on MRI were associated with cognitive impairment. Whilst further investigation will be required to confirm causality, use of this finding as a risk stratification biomarker is promising.

The genetic architecture of brain structure and function is largely unknown. To investigate this, we carried out genome-wide association studies of 3,144 functional and structural brain imaging phenotypes from UK Biobank (discovery dataset 8,428 subjects). Here we show that many of these phenotypes are heritable. We identify 148 clusters of associations between single nucleotide polymorphisms and imaging phenotypes that replicate at P < 0.05, when we would expect 21 to replicate by chance. Notable significant, interpretable associations include: iron transport and storage genes, related to magnetic susceptibility of subcortical brain tissue; extracellular matrix and epidermal growth factor genes, associated with white matter micro-structure and lesions; genes that regulate mid-line axon development, associated with organization of the pontine crossing tract; and overall 17 genes involved in development, pathway signalling and plasticity. Our results provide insights into the genetic architecture of the brain that are relevant to neurological and psychiatric disorders, brain development and ageing.

There is strong evidence for brain-related pathologies in COVID-19, some of which could be a consequence of viral neurotropism. The vast majority of brain imaging studies so far have focused on qualitative, gross pathology of moderate to severe cases, often carried out on hospitalised patients. It remains unknown however whether the impact of COVID-19 can be detected in milder cases, in a quantitative and automated manner, and whether this can reveal a possible mechanism for the spread of the disease. UK Biobank scanned over 40,000 participants before the start of the COVID-19 pandemic, making it possible to invite back in 2021 hundreds of previously-imaged participants for a second imaging visit. Here, we studied the effects of the disease in the brain using multimodal data from 782 participants from the UK Biobank COVID-19 re-imaging study, with 394 participants having tested positive for SARS- CoV-2 infection between their two scans. We used structural and functional brain scans from before and after infection, to compare longitudinal brain changes between these 394 COVID- 19 patients and 388 controls who were matched for age, sex, ethnicity and interval between scans. We identified significant effects of COVID-19 in the brain with a loss of grey matter in the left parahippocampal gyrus, the left lateral orbitofrontal cortex and the left insula. When looking over the entire cortical surface, these results extended to the anterior cingulate cortex, supramarginal gyrus and temporal pole. We further compared COVID-19 patients who had been hospitalised (n=15) with those who had not (n=379), and while results were not significant, we found comparatively similar findings to the COVID-19 vs control group comparison, with, in addition, a greater loss of grey matter in the cingulate cortex, central nucleus of the amygdala and hippocampal cornu ammonis (all |Z|>3). Our findings thus consistently relate to loss of grey matter in limbic cortical areas directly linked to the primary olfactory and gustatory system. Unlike in post hoc disease studies, the availability of pre- infection imaging data helps avoid the danger of pre-existing risk factors or clinical conditions being mis-interpreted as disease effects. Since a possible entry point of the virus to the central nervous system might be via the olfactory mucosa and the olfactory bulb, these brain imaging results might be the in vivo hallmark of the spread of the disease (or the virus itself) via olfactory and gustatory pathways.

UK Biobank is a major prospective epidemiological study that is carrying out detailed multimodal brain imaging on 100,000 participants, and includes genetics and ongoing health outcomes. As a step forwards in understanding genetic influence on brain structure and function, in 2018 we published genome-wide associations of 3,144 brain imaging-derived phenotypes, with a discovery sample of 8,428 UKB subjects. Here we present a new open resource of GWAS summary statistics, resulting from a greatly expanded set of genetic associations with brain phenotypes, using the 2020 UKB imaging data release of approximately 40,000 subjects. The discovery sample has now almost tripled (22,138), the number of phenotypes increased to 3,935 and the number of SNPs increased to 17 million. For the first time, we include associations on the X chromosome. Previously we had found 148 replicated clusters of associations between genetic variants and imaging phenotypes; here we find 692 replicating clusters of associations, including 12 on the X chromosome. We describe some of the newly found associations, focussing particularly on the X chromosome. All summary statistics are openly available for interactive viewing and download on the “BIG40” open web server.